Description Usage Arguments Details Value Author(s) See Also Examples

Compute a weighted version of the empirical cumulative distribution function.

1 |

`x` |
Numeric vector of observations. |

`weights` |
Numeric vector of non-negative weights
for |

This is a modification of the standard function `ecdf`

allowing the observations `x`

to have weights.

The weighted e.c.d.f. (empirical cumulative distribution function)
`Fn`

is defined so that, for any real number `y`

, the value of
`Fn(y)`

is equal to the total weight of all entries of
`x`

that are less than or equal to `y`

. That is
`Fn(y) = sum(weights[x <= y])`

.

Thus `Fn`

is a step function which jumps at the
values of `x`

. The height of the jump at a point `y`

is the total weight of all entries in `x`

number of tied observations at that value. Missing values are
ignored.

If `weights`

is omitted, the default is equivalent to
`ecdf(x)`

except for the class membership.

The result of `ewcdf`

is a function, of class `"ewcdf"`

,
inheriting from the classes `"ecdf"`

and `"stepfun"`

.
The class `ewcdf`

has methods for `print`

and `quantile`

.
The inherited class `ecdf`

has methods for `plot`

and `summary`

.

A function, of class `"ewcdf"`

, inheriting from
`"ecdf"`

and `"stepfun"`

.

.

`ecdf`

.

1 2 3 |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.